The modern communications era has brought about a tremendous expansion of wireline and wireless networks. Computer networks, television networks, and telephony networks are experiencing an unprecedented technological expansion, fueled by consumer demand. Wireless and mobile networking technologies have addressed related consumer demands, while providing more flexibility and immediacy of information transfer.
Current and future networking technologies continue to facilitate ease of information transfer and convenience to users. Due to the now ubiquitous nature of electronic communication devices, people of all ages and education levels are utilizing electronic devices to communicate with other individuals or contacts, receive services and/or share information, media and other content. One area in which there is a demand to increase ease of information transfer relates to compressed data.
Currently, compression of data may require significant computation resources. However, mobile devices typically have only limited amount of battery energy available to perform compression of data. As a consequence, energy-efficient compression methods that require minimal computing power and generate highly compressed images may be beneficial to conserve computational resources of mobile devices. At present, oftentimes the Nyquist sampling frequency may be used to compress multimedia content. However, the Nyquist sampling frequency generally densely samples data which may require sampling over large amounts of data (e.g., sampling every pixel of an image) for reconstruction or decompression of original data. Dense sampling typically consumes a large amount of computing resources, which may constrain resources of mobile devices.
As such, it may be more efficient to provide a mechanism of performing sampling and storing of compressed content utilizing information that allows practically all compressed data to be reconstructed from much smaller amounts of sampled information than what the Nyquist sampling frequency and other conventional compression methods typically require.
In view of the foregoing drawbacks, it may be beneficial to provide an efficient and reliable mechanism to compress and decompress data which may conserve computational resources of a communication device.